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Computer Vision Training Courses

Local, instructor-led live Computer Vision training courses demonstrate through interactive discussion and hands-on practice the basics of Computer Vision as participants step through the creation of simple Computer Vision apps.

Computer Vision training is available as "onsite live training" or "remote live training". The Philippines onsite live Computer Vision trainings can be carried out locally on customer premises or in NobleProg corporate training centers. Remote live training is carried out by way of an interactive, remote desktop.

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Testimonials

★★★★★

★★★★★

I genuinely enjoyed the hands-on approach.

Kevin De Cuyper

Course: Computer Vision with OpenCV

The easy use of the VideoCapture functionality to acquire video images from laptop camera.

HP Printing and Computing Solutions, Sociedad Limitada Unipe

Course: Computer Vision with OpenCV

I enjoyed the advises given by the trainer about how to use the tools. This is something that can't be got from the internet and are very useful.

HP Printing and Computing Solutions, Sociedad Limitada Unipe

Course: Computer Vision with OpenCV

I enjoyed the advises given by the trainer about how to use the tools. This is something that can't be got from the internet and are very useful.

SimpleCV is an open source framework — meaning that it is a collection of libraries and software that you can use to develop vision applications. It lets you work with the images or video streams that come from webcams, Kinects, FireWire and IP cameras, or mobile phones. It’s helps you build software to make your various technologies not only see the world, but understand it too.

Audience

This course is directed at engineers and developers seeking to develop computer vision applications with SimpleCV.

Pattern Matching is a technique used to locate specified patterns within an image. It can be used to determine the existence of specified characteristics within a captured image, for example the expected label on a defective product in a factory line or the specified dimensions of a component. It is different from "Pattern Recognition" (which recognizes general patterns based on larger collections of related samples) in that it specifically dictates what we are looking for, then tells us whether the expected pattern exists or not.

Marvin is an extensible, cross-platform, open-source image and video processing framework developed in Java. Developers can use Marvin to manipulate images, extract features from images for classification tasks, generate figures algorithmically, process video file datasets, and set up unit test automation.

Format of the course The basic principles of image analysis, video analysis and the Marvin Framework are first introduced. Students are given project-based tasks which allow them to practice the concepts learned. By the end of the class, participants will have developed their own application using the Marvin Framework and libraries.

This instructor-led, live training introduces the software, hardware, and step-by-step process needed to build a facial recognition system from scratch. Facial Recognition is also known as Face Recognition.

The hardware used in this lab includes Rasberry Pi, a camera module, servos (optional), etc. Participants are responsible for purchasing these components themselves. The software used includes OpenCV, Linux, Python, etc.

By the end of this training, participants will be able to:

- Install Linux, OpenCV and other software utilities and libraries on a Rasberry Pi.- Configure OpenCV to capture and detect facial images.- Understand the various options for packaging a Rasberry Pi system for use in real-world environments.- Adapt the system for a variety of use cases, including surveillance, identity verification, etc.

Computer Vision is a field that involves automatically extracting, analyzing, and understanding useful information from digital media. Python is a high-level programming language famous for its clear syntax and code readibility.

In this instructor-led, live training, participants will learn the basics of Computer Vision as they step through the creation of set of simple Computer Vision application using Python.

By the end of this training, participants will be able to:

- Understand the basics of Computer Vision- Use Python to implement Computer Vision tasks- Build their own face, object, and motion detection systems

Audience

- Python programmers interested in Computer Vision

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice

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